Search Results for author:
Found 16 papers, 8 papers with code
Tendency-driven Mutual Exclusivity for Weakly Supervised Incremental Semantic Segmentation
However, a scenario usually arises where a pixel is concurrently predicted as an old class by the pre-trained segmentation model and a new class by the seed areas.
Appeal: Allow Mislabeled Samples the Chance to be Rectified in Partial Label Learning
In partial label learning (PLL), each instance is associated with a set of candidate labels among which only one is ground-truth.
Bridging Synthetic and Real Worlds for Pre-training Scene Text Detectors
Existing scene text detection methods typically rely on extensive real data for training.
High-performance Power Allocation Strategies for Active IRS-aided Wireless Network
Due to its slow linear convergence from iterative GA, the proposed ESMPI-GA is high-complexity.
SVCNet: Scribble-based Video Colorization Network with Temporal Aggregation
It addresses three common issues in the scribble-based video colorization area: colorization vividness, temporal consistency, and color bleeding.
Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks
Moreover, it is verified that the proposed HP-SDR-FP method perform better than WF-GPI-GRR method in terms of rate performance.
Three High-rate Beamforming Methods for Active IRS-aided Wireless Network
To fully exploit the amplifying gain achieved by active IRS, two high-rate methods, maximum ratio reflecting (MRR) and selective ratio reflecting (SRR) are presented, which are motivated by maximum ratio combining and selective ratio combining.
H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection
Oriented object detection emerges in many applications from aerial images to autonomous driving, while many existing detection benchmarks are annotated with horizontal bounding box only which is also less costive than fine-grained rotated box, leading to a gap between the readily available training corpus and the rising demand for oriented object detection.
D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration
Night imaging with modern smartphone cameras is troublesome due to low photon count and unavoidable noise in the imaging system.
A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction
Next, we summarize the existing label-efficient image segmentation methods from a unified perspective that discusses an important question: how to bridge the gap between weak supervision and dense prediction -- the current methods are mostly based on heuristic priors, such as cross-pixel similarity, cross-label constraint, cross-view consistency, and cross-image relation.
ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
On this basis, we formulate predictions as a mapping from parents' genetic factors to children's genetic factors, and disentangle them from external and variety factors.
Age-Invariant Face Recognition
Image-to-Image Translation
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ContrastMask: Contrastive Learning to Segment Every Thing
In this framework, annotated masks of seen categories and pseudo masks of unseen categories serve as a prior for contrastive learning, where features from the mask regions (foreground) are pulled together, and are contrasted against those from the background, and vice versa.
SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging
Besides, the multimodal attention module is proposed to adaptively capture valuable information from multimodal data for the specific sleep stage.
Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning
In this paper, we develop a computation efficient yet accurate network based on the proposed attentive auxiliary features (A$^2$F) for SISR.
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
Scene-adaptive Coded Apertures Imaging
Firstly, we capture the scene with a pinhole and analyze the scene content to determine primary edge orientations.
